Jobs in the data field can indeed be taken by people who do not have previous data background, but of course the journey has a route that is not easy either. That’s why it’s important to have strong principles to focus on studying data. The principle can be analogous to a compass, a compass can be a direction that can guide where life will be under. Without principles we will not be able to move because we ourselves do not know what we want to go.
Adhering to the principle is not easy. We must be committed to continue to walk with the principles of life that we have set. Of course, learning must also have strong principles so that we can be consistent and also know the right direction of learning. Based on research conducted by a psychologist at Stanford University, it is stated that the mindset or mindset is one of the keys to success. Not without reason, mindset or perspective will affect how we live and see the situation.
Here are the must-have principles if you want to become a data expert:
The growth mindset can be interpreted as the mindset of someone who understands that the abilities or talents he has since childhood are a start. They believe that these abilities and talents can continue to develop with hard work and dedication. They instill the mindset to continually learn and understand the world.
This principle is very important to have when you start learning data or when you go directly to the field. Of course, when you work as a data expert you will continue to learn every day whether you are analyzing or collecting new data. Plus technology is growing every day, the way that is done now may no longer be effectively used in the next 50 years. Therefore, the growth mindset can be an important aspect when working or studying as a data expert.
2. Never Give Up
Who doesn’t know KFC? Surely we are familiar when we hear about KFC fast food restaurants, KFC founder Colonel Sander has experienced more than 1000 rejections in spreading his chicken recipe for the first time. However, Colonel Sanders never gave up on distributing chicken recipes and in the end his chicken recipe became a brand that spread throughout the world.
In learning also must hold firmly to this principle. When you work as a Data Scientist or Data Analyst you not only learn about data but also you are required to understand business, statistics and so on. If you don’t hold on to the principle of never giving up, you will be stuck in the middle of the road.
3.Focus on One Thing
As a Data Expert you will be presented with millions of data every day. From the millions of data, you are required to be able to analyze the right strategy based on the millions of data that have been provided. Moreover, you also have to test whether this strategy is the best strategy. This is where you will also find various combinations of Python code, SQL to statistics to get the right analysis.
Therefore focus is very important if you want to become an expert in the field of data. Focus can also minimize the possibility of errors. You really need a good focus at work. So the possibility of mistakes that often come due to carelessness will decrease for sure. You won’t even make a mistake if you work with a better focus than before.
4. Start Your Career Become a Data Expert with DQLab!
DQLab is a Data Science learning center that offers online courses for those of you who want to start learning Data Science. DQLab itself has produced data practitioners who are proficient in their fields. With DQLab you will learn in a structured manner with case studies and data that are in accordance with those in the field. DQLab also provides a forum for sharing with 95,000++ members of DQLab, as well as with expert data practitioners.
DQLab offers a structured, project-based learning method that is suitable for beginners who are just starting to learn Data Science. DQLab uses 4 learning concepts.
Basic concepts of Data Science
Apply the theories that have been learned through the Live Code Editor.
Build a data portfolio with case studies that have been approved by data experts
DQLab provides seminar sessions filled with experienced Industrial Practitioners who can build relationships with other Data Scientists.
By Yohanes Ricky & Annissa Widya | DQLab